理解印度劳动力市场:以数据为中心的方法

K. Shabana, Tony Gracious, H. Subramonian
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引用次数: 1

摘要

印度每年培养150万名工程师。确定影响这些工程师的工资和工作的重要因素,可以帮助我们了解劳动力市场的低效率或技能差距,这将对政策制定和建设性干预非常有用。使用不同的机器学习技术对包括员工简介及其就业结果的数据集进行了工资预测建模。通过决策树分析、特征分析、相关分析和t检验,找出影响候选人年薪的显著因素。根据员工工资、职位和工作城市生成的可视化显示了有趣的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Understanding the Indian labour market: A data-centric approach
India produces 1.5 million engineers every year. Identifying the significant factors that influence the salary and the jobs these engineers are offered can help us understand the inefficiencies or skill gaps in the labour market, which will be extremely useful for policy making and constructive interventions. Predictive modelling of salary was performed using different machine learning techniques on a data set that included both employee profiles and their employment outcomes. Decision tree analysis, feature analysis, correlation analysis and t-test were performed to identify the significant factors that influenced the annual salary offered to a candidate. Visualizations generated based on employee salary, designation and job city revealed interesting insights.
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